@article{10.11648/j.sf.20250603.12,
  author = {Rudwan Yasin Abrahim and Abulmejid Gudu and Dawit Abdi and Kedir Nuredin and Shalo Alemu and Kidist Mehari Azene and Bethelhem Fekadeselassie Lemma and Olifan Getachew},
  title = {Glycemic Control and Associated Factors Among Diabetics on Active Follow up at Public Hospitals of Harar, Eastern Ethiopia
},
  journal = {Science Frontiers},
  volume = {6},
  number = {3},
  pages = {57-71},
  doi = {10.11648/j.sf.20250603.12},
  url = {https://doi.org/10.11648/j.sf.20250603.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sf.20250603.12},
  abstract = {Background: Poor glycemic control leads to medical consequences, whereas effective glycemic control minimizes acute and chronic complications and death due to Diabetes Mellitus. In some literatures, the prevalence of poor glycemic control approaches 80%. Considering the seriousness of the problem, there is a knowledge gap in the study area regarding the prevalence of poor glycemic control and the underlying causes. Therefore, this study aimed assess the status of poor glycemic control and associated factors among diabetics on active follow up at public hospitals of Harar, Eastern Ethiopia from February 1-28, 2023. Methods: Cross-sectional study design was employed. Proportionate stratified sampling technique was applied to obtain 405 diabetic patients on active follow. Data was entered in to EpiData software version 4.6, then exported to STATA software version 17 for analysis. Three consecutive months’ average fasting blood glucose level was used to determine glycemic control. Explanatory variables with p value less than 0.20 in bivariate logistic regression analysis were entered into the multivariable logistic regression analysis model. Every variable with P-values less than 0.05 in the multivariable logistic model was considered as statistically significant. Results: Mean age of pediatric participants was 11.3 years ± 4.1 SD while the mean age of adult participants was 49.8 years ± 14.7 SD. Females made up 52.1% of the total. Overall prevalence of poor glycemic control was 73.6% (95%CI: 69-77.7). Age >50 years (AOR = 3.01; 95% CI: 1.10-8.24), being Unemployed (AOR = 6.06; 95% CI: 1.43-25.60), poor level of adherence to blood sugar testing (AOR = 3.95; 95% CI: 1.61-9.70), duration > 4 years on DM treatment (AOR) = 2.23; 95%CI: 1.001-4.98) and high level of total serum triglyceride (AOR = 10.37; 95%CI: 4.29-25.06) significantly increased the odds of poor glycemic control. Conclusion: There is high prevalence of poor glycemic control in the study area. The factors with statistically significant effects on poor glycemic control included age ≥ 50 years, unemployment, low blood sugar testing compliance, longer duration on treatment, and high levels of total serum triglycerides. I rcommend especial attention to the elderlies, unemployeds and those with long duration on treatment.},
 year = {2025}
}

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TY  - JOUR
T1  - Glycemic Control and Associated Factors Among Diabetics on Active Follow up at Public Hospitals of Harar, Eastern Ethiopia

AU  - Rudwan Yasin Abrahim
AU  - Abulmejid Gudu
AU  - Dawit Abdi
AU  - Kedir Nuredin
AU  - Shalo Alemu
AU  - Kidist Mehari Azene
AU  - Bethelhem Fekadeselassie Lemma
AU  - Olifan Getachew
Y1  - 2025/08/18
PY  - 2025
N1  - https://doi.org/10.11648/j.sf.20250603.12
DO  - 10.11648/j.sf.20250603.12
T2  - Science Frontiers
JF  - Science Frontiers
JO  - Science Frontiers
SP  - 57
EP  - 71
PB  - Science Publishing Group
SN  - 2994-7030
UR  - https://doi.org/10.11648/j.sf.20250603.12
AB  - Background: Poor glycemic control leads to medical consequences, whereas effective glycemic control minimizes acute and chronic complications and death due to Diabetes Mellitus. In some literatures, the prevalence of poor glycemic control approaches 80%. Considering the seriousness of the problem, there is a knowledge gap in the study area regarding the prevalence of poor glycemic control and the underlying causes. Therefore, this study aimed assess the status of poor glycemic control and associated factors among diabetics on active follow up at public hospitals of Harar, Eastern Ethiopia from February 1-28, 2023. Methods: Cross-sectional study design was employed. Proportionate stratified sampling technique was applied to obtain 405 diabetic patients on active follow. Data was entered in to EpiData software version 4.6, then exported to STATA software version 17 for analysis. Three consecutive months’ average fasting blood glucose level was used to determine glycemic control. Explanatory variables with p value less than 0.20 in bivariate logistic regression analysis were entered into the multivariable logistic regression analysis model. Every variable with P-values less than 0.05 in the multivariable logistic model was considered as statistically significant. Results: Mean age of pediatric participants was 11.3 years ± 4.1 SD while the mean age of adult participants was 49.8 years ± 14.7 SD. Females made up 52.1% of the total. Overall prevalence of poor glycemic control was 73.6% (95%CI: 69-77.7). Age >50 years (AOR = 3.01; 95% CI: 1.10-8.24), being Unemployed (AOR = 6.06; 95% CI: 1.43-25.60), poor level of adherence to blood sugar testing (AOR = 3.95; 95% CI: 1.61-9.70), duration > 4 years on DM treatment (AOR) = 2.23; 95%CI: 1.001-4.98) and high level of total serum triglyceride (AOR = 10.37; 95%CI: 4.29-25.06) significantly increased the odds of poor glycemic control. Conclusion: There is high prevalence of poor glycemic control in the study area. The factors with statistically significant effects on poor glycemic control included age ≥ 50 years, unemployment, low blood sugar testing compliance, longer duration on treatment, and high levels of total serum triglycerides. I rcommend especial attention to the elderlies, unemployeds and those with long duration on treatment.
VL  - 6
IS  - 3
ER  - 

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